title: A niche-based modeling approach to phytoplankton community assembly rules.
abstract: Six niche-based models proposed by Tokeshi, based on different assumptions of resource allocation by species, were fitted on phytoplankton relative abundance distributions, and potential environmental and biotic factors supporting the applicability of the fitted models were discussed. Overall 16 assemblages corresponding to different sampling times, various environmental conditions, and resource regimes within a year were fitted to the models. Phytoplankton biovolume was used as a measure of abundance, and a randomization test was applied to compare the model fit to the field data. The majority of the phytoplankton assemblages (11 of 16) were successfully described by the Random Fraction model, which is based on the theoretical assumption that resource is apportioned by the species in a random way. Only a few assemblages (three of 16), characterized by extremes in resource availability or disturbance, were not fitted by any of the models. The Random Fraction model in particular was rejected due to a steep slope during the first ranks, while the rest of the distribution remained relatively even, providing further evidence of resilience in phytoplankton communities. Although larger cells seem to have the potential to develop higher biomass, it seems that other factors, including the surface-to-volume ratio, counterbalance this advantage, resulting in a random-like behaviour in resource acquisition by phytoplankton, irrespective of cell size or species identity.
authors.affiliation: Laboratoire des Ecosystèmes Lagunaires, Université Montpellier II, Place Eugène Bataillon, 34095, Montpellier Cedex 5, France. spathari@marine.aegean.gr
authors.forename: Sofie
authors.initials: S
authors.lastname: Spatharis
authors.forename: David
authors.initials: D
authors.lastname: Mouillot
authors.forename: Thang Do
authors.initials: TD
authors.lastname: Chi
authors.forename: Daniel B
authors.initials: DB
authors.lastname: Danielidis
authors.forename: George
authors.initials: G
authors.lastname: Tsirtsis
mesh_terms: D017753:Ecosystem; D008954:Models, Biological; D010839:Phytoplankton / Q000502:physiology*; D011157:Population Dynamics; D013997:Time Factors